Abstract
Background
Fatigue is reported as one of the most disabling symptoms and is common among persons living with late effects of polio. Although fatigue has been studied in the context of people living with late effects of polio, there is a lack of knowledge concerning the association of fatigue and variables of importance for participation in daily life. Therefore, the aim of this study was to explore possible factors associated with fatigue among persons with late effects of polio in Sweden.
Methods
This retrospective registry study consisted of 89 persons with late effects of polio living in Sweden. Fatigue was measured with the Multidimensional Fatigue Inventory (MFI-20) scale, Swedish version. Pearson’s correlation coefficient was used to analyse the correlation between the factors and fatigue, and a multiple linear regression was carried out to explore factors for fatigue.
Results
Fatigue statistically significantly correlated with age (r = 0.234, p < 0.05) and the use of mobility assistive devices (r = 0.255, p < 0.05). The multiple linear regression model showed that the factors age (β = 0.304, p < 0.019) and mobility assistive devices (β = 0.262, p < 0.017) were associated with fatigue among persons living with late effects of polio, and the model partly explained 14% of the variation of fatigue.
Conclusions
Fatigue could partly be explained by the extent of using mobility assistive devices and age. Healthcare professionals should provide and demonstrate the importance of assistive devices to ensure management of fatigue in persons living with late effects of polio.
Keywords: Post poliomyelitis syndrome, Occupational therapy, Multidimensional fatigue inventory (MFI-20) scale, Cross-sectional studies
Background
Fatigue is a common symptom reported among persons living with late effects of polio [1–3]. There are ambiguously definitions of fatigue in the literature [4–7]. It can be assessed in different ways [5], and is seen as a complex phenomenon with a large number of conceptualizations [6]. Fatigue can be defined as an overwhelming sense of tiredness, a lack of energy, and feeling of exhaustion, that can be associated with impaired physical and/or cognitive function [6]. In this study, fatigue is defined as an overwhelming sense of tiredness, a lack of energy and a feeling of exhaustion that may be associated with the impaired physical and/or cognitive function [6]. Fatigue may be either peripheral or central depending on where in the nervous system it originates [8], and there are several types of fatigue, such as general, physical or muscle fatigue [3].
About 60–85% of persons living with late effects of polio face recurrence of the original polio related manifestations as well as new symptoms, suggesting new health problems [9]. This state is usually named post-polio syndrome (PPS). People may experience late effects of polio without being diagnosed with PPS [3]. Several terms have been used to describe the symptoms followed by polio, such as ‘the late effects of polio’ and ‘post-polio sequelae’ [10]. In this study the term ‘the late effects of polio’ is used. According to Gawne and Halstead [10], the specific criteria for PPS are: a prior episode of paralysis confirmed by history, physical exam, and findings on an electromyogram (EMG); a period of neurological recovery followed by an extended interval of neurological and functional stability, usually lasting 20 years or more; and a gradual or abrupt onset of new neurogenic, non-disuse weakness in previously affected and/or unaffected muscles. These symptoms may or may not be accompanied by other new health problems, such as excessive fatigue, muscle pain, joint pain, decreased endurance, decreased function, and atrophy. Other neurologic, medical and orthopaedic conditions that might cause the health problems mentioned above must be excluded [10].
Persons living with late effects of polio may face restrictions on participating in different areas of life [11, 12]. Restrictions have been identified in occupations related to their family role, work and education, and to autonomy outdoors [11]. Dependence in occupations such as cleaning, transportation, and shopping has also been associated with restrictions in daily life activities [12]. Fatigue has been pointed out as an invisible disabling symptom affecting a person’s ability to perform occupations and limiting mastery of daily occupations [13]. It has also been reported that persons living with late effects of polio act at close to maximum of their capacity, and fatigue has been found to be related to muscle overuse [14, 15]. The perceived fatigue can remain for days after fatiguing exercise but without reduction. This phenomenon called low frequency fatigue can be described as persisting for prolonged periods of time before full capacity has returned [16, 17].
Earlier research [11–13, 18, 19] has identified various factors as important when exploring fatigue in everyday life among persons living with late effects of polio. The explanatory power of these factors in relation to fatigue has not yet been captured. In this study we explored fatigue in relation to the factors age, gender, country of birth, occupational/employment level and, the use of mobility assistive devices. Research has shown that there are inequities in health status associated with country of birth [18, 19]. The level of occupation/employment has been shown to be associated with fatigue [20]. Studies [21, 22] have shown that persons living with late effects of polio experience tiredness which restricts participation at work. These limitations resulted in both physical and psychosocial distress created by an internal conflict between what the person want to do and what they are able to do [21, 22]. Moreover, another factor of importance for fatigue is the use of assistive devices, which has shown to positively affect ability and reduce perceived difficulties [12]. Research [23] has shown that persons living with late effects of polio could experience pain and fatigue when they hesitated to start using assistive devices, in particularly mobility devices. To get a better understanding of factors associated with fatigue, the objective was to explore possible factors associated with fatigue among persons with late effects of polio in Sweden.
Methods
Sampling and participants
This retrospective registry study used patient data from a clinical database with persons with late effects of polio from the Polio Clinic, Sahlgrenska University Hospital, Gothenburg, Sweden. The clinic has encountered more than 900 persons with polio since the clinic opened 1994, and since that time different questionnaires have been used [24]. In the present study, data from persons that responded to a questionnaire concerning fatigue were identified from the clinical database. The following inclusion criteria were used: (i) persons aged 18 years or older, and (ii) with late effects of polio. In a total, 89 persons were included in the study; those who had answered the fatigue questionnaire. Due to internal dropouts on different items the calculations were based on slightly different sample size (see notes in Tables 2, 3, 4, and 5).
Table 2.
Characteristics of participants (n = 89)
| Participants | n (%) |
|---|---|
| Gender | |
| Female | 48 (54) |
| Age (years) | |
| Range | 19–93 years |
| 19–29 | 5 (6) |
| 30–49 | 12 (13) |
| 50–69 | 40 (45) |
| 70 ≥ | 32 (36) |
| Country of birth | |
| Nordic countries | 65 (73) |
| Outside the Nordic countries | 24 (27) |
| Post-polio syndrome (PPS) | 88 (99) |
| Occupation/employment level | |
| Unemployed | 6 (7) |
| Working ≤50% | 5 (6) |
| Working 100% | 28 (31) |
| Early retirement | 7 (8) |
| Retired | 43 (48) |
| Use of assistive devices | |
| No walking devices | 59 (66) |
| Crutches, cane and/or walker | 20 (22) |
| Wheelchair occasionally | 5 (6) |
| Wheelchair | 5 (6) |
Table 3.
Percentage distribution and number of participants rating fatigue
| MFI-20 Subscales | n (%) |
|---|---|
| General fatigue (4 items) (n = 89) | 79 (89) |
| Physical fatigue (4 items) (n = 89) | 80 (90) |
| Mental fatigue (4 items) (n = 88) | 45 (51) |
| Reduced activity (4 items) (n = 87) | 73 (84) |
| Reduced motivation (4 items) (n = 87) | 45 (52) |
Table 4.
Correlation between fatigue and the factors (n = 85)
| Variables | Fatigue | Gender | Age | Country of birth | Occupation/employment level |
|---|---|---|---|---|---|
| Fatigue | 1 | ||||
| Gender | −0.046 | 1 | |||
| Age | 0.234* | −0.073 | 1 | ||
| Country of birth | −0.189 | 0.211 | −0.729** | 1 | |
| Occupation/employment level | −0.017 | −0.158 | −0.548** | 0.278* | 1 |
| Mobility assistive devices | 0.255* | −0.004 | −0.090 | −0.74 | 0.238* |
*p < 0.05, **p < 0.01
Table 5.
Multiple linear regression for fatigue and the factors (n =85)
| Independent variables | β | 95% CI | p-value |
|---|---|---|---|
| Age | 0.304 | 0.38–4.04 | 0.019 |
| Gender | −0.009 | −2.70–2.28 | 0.932 |
| Occupation/employment level | 0.086 | −2.20–4.36 | 0.514 |
| Mobility assistive devices | 0.262 | 0.63–6.22 | 0.017 |
R 2 = 14%
Assessments
Data were collected between 2008 and 2011. The dependent variable of fatigue was explored and analysed in relation to the following factors; gender, age, country of birth, occupation/employment level, and the use of mobility assistive devices.
Dependent variable
Fatigue was assessed using the Swedish version of the Multidimensional Fatigue Inventory (MFI-20) [5], which is a self-administered questionnaire with a total of 20 items. The MFI-20 assesses a person’s self-rated fatigue in the following five subscales: General Fatigue (GF), Physical Fatigue (PF), Mental Fatigue (MF), Reduced Motivation (RM), and Reduced Activity (RA). The subscales and the 20 items are presented in Table 1. The level of fatigue can be scored with a minimum of 4 points to a maximum of 20 points on the 5-point Likert scale (1 = yes, that is true, 2–4 = no verbal specification, and 5 = no, that is not true). A total fatigue score ranging from 20 to 100 can be calculated as the sum of the five subscales scores. A higher score represents higher levels of fatigue. The Swedish version of the MFI-20 has been psychometrically tested, showing good psychometrically properties in different settings (persons with post-polio, cancer, fibromyalgia, chronic widespread pain and in a healthy population) [5, 25, 26].
Table 1.
Subscales and items within the MFI-20
| MFI-20 Subscales | Item nr | Item |
|---|---|---|
| General fatigue | 1 | I feel fit |
| 5 | I feel tired | |
| 12 | I am rested | |
| 16 | I tire easily | |
| Physical fatigue | 2 | Physically I feel only able to do a little |
| 8 | Physically I can take on a lot | |
| 14 | Physically I feel I am in a bad condition | |
| 20 | Physically I feel I am in an excellent condition | |
| Mental fatigue | 7 | When I am doing something, I can keep my thought on it |
| 11 | I can concentrate well | |
| 13 | It takes a lot of effort to concentrate on things | |
| 19 | My thoughts easily wander | |
| Reduced activity | 3 | I feel very active |
| 6 | I think I do a lot in a day | |
| 10 | I think I do very little in a day | |
| 17 | I get little done | |
| Reduced motivation | 4 | I feel like doing all sorts of nice things |
| 9 | I dread having to do things | |
| 15 | I have a lot of plans | |
| 18 | I don’t feel like doing anything |
In this study, fatigue was dichotomized into no reported fatigue (level one to two on the scale), and reported fatigue (level three to five on the scale) only on a sub-scale level when analysing the percentage distribution of participants rating fatigue. To simplify the dichotomization into no reported fatigue and reported fatigue some of the items scale (items 2, 5, 9, 10, 13, 14, 16, 17, 18 and 19) were converted to the reverse. In contrast, the total original score for fatigue was used in the correlation analysis and in the regression model.
Factors
Basic demographics of the participants were explored with gender and age, where age was divided into four following age groups: 18–29 years, 30–49 years, 50–69 years, equal and over 70 years. Country of birth the participants was divided in the two groups: persons born in Nordic countries (Sweden, Denmark, Finland and Norway), and persons born outside the Nordic countries (Afghanistan, Bolivia, Chile, Ethiopia, countries of the former Yugoslavia, Kosovo, Macedonia, the Philippines, Gambia, Iraq, Iran, Lebanon, Nigeria, Peru, Sierra Leone, Somalia, Syria, Tunisia, and Turkey). Occupation/employment level of the persons was explored by forming the two groups: working (working fulltime, working halftime or less), and not working ((unemployed, early retirement (pension before 65 years of age) and retired (pension at 65 years of age, or older)). The use of mobility assistive devices was divided into two following groups: not using mobility assistive devices and using mobility assistive devices (crutches, cane and/or walker, wheelchair occasionally, and wheelchair).
Statistical analysis
Descriptive statistics were carried out on the participants’ characteristics and fatigue. Pearson’s correlation coefficient was used to analyse the strength in correlation between variables. A multiple linear regression was used to explore explanatory factors for fatigue. Prior to analyzing the multiple linear regression, the criteria of this method was reviewed for the nature of the underlying relationships and residuals. Data were analysed using the IBM SPSS Statistics, version 22.0 (IBM Corp., Armonk, NY, 2013).
Results
Characteristics of the participants
The mean age of the participants was 61 years (age range 19–93). Approximately half of the sample was female (54%), and the majority had PPS (99%). The occupation/employment level varied from unemployed (7%), working part time (6%), working full time (31%), early retirement (8%), and retired (48%). More than half of the participants used no mobility walking devices (66%), and among the participants who used mobility assistive devices, the use of assistive devices ranged from walking with crutches, cane and/or walker to using a wheelchair (Table 2).
Fatigue
Overall, participants rated a high grade of fatigue in three of the five sub-scales of the MFI-20. The majority reported physical fatigue (90%), general fatigue (89%) and reduced activity (84%). Moreover, half of the sample reported mental fatigue and reduced motivation (Table 3).
Correlation between fatigue and the factors
Fatigue positively and weakly correlated with age (r = 0.234, p < 0.05) and using mobility assistive devices (r = 0.255, p < 0.05), meaning that the older participants reported more fatigue than the younger and that the participants using mobility assistive devices reported less fatigue. The use of mobility assistive devices also correlated positively and weakly with occupational employment level (r = 0.238, p < 0.05) meaning that participants not working used mobility assistive devices to a lesser extent. Finally, there was a weak and positive correlation between country of birth and occupational/employment level (r = 0.278, p < 0.01) indicating that persons born in the Nordic countries were older and so thereby more often retired (Table 4).
Linear regression model
The multiple linear regression model showed that the factors age (β = 0.304, p < 0.019) and the use of mobility assistive devices (β = 0.262, p < 0.017) partially explained fatigue among persons living with late effects of polio. This result indicated that both high age and people not using mobility assistive devices reported more fatigue. There remaining two factors did not significantly explain fatigue in the final model. The regression model explained 14% of the variation in self-rated fatigue (Table 5).
Discussion
The aim of the present study was to explore possible factors associated with fatigue among persons with late effects of polio in Sweden. The main results were that persons not using mobility assistive devices and with high age reported more fatigue. However, the variation in fatigue could only be explained by 14% of the factors within the regression model.
In the present study, one of the factors that partly could explain the dependent variable of fatigue was the use of mobility assistive devices. A possible explanation for this could be that persons using mobility assistive devices stored their energy by simply using their mobility assistive devices, which in turn had a positive effect on the people’s self-rated fatigue. Also, persons not using mobility assistive devices might consume more energy when moving around, which may have resulted in an increased subjective feeling of fatigue. This finding of the importance of using mobility assistive devices is in line with a previous study [23], which showed that pain and fatigue could be associated with a lack of using mobility assistive devices among persons living with late effects of polio. On the other hand, another possible explanation could be that the persons with less fatigue did not need to use mobility assistive devices in a larger extent. Thus, the degree of fatigue did not lead to a need of using mobility assistive devices.
The findings from the present study indicated that age could contribute to explain fatigue among persons living with late effect of polio. This result may not only represent persons living with late effects of polio, it could also be transferred to people living with disability where fatigue is one of the symptoms. Moreover, gender and occupation/employment level could not significantly explain fatigue in the multiple regression model. This is in contrast to what has been shown in the general population, where females had higher mean values in all MFI-20 subscales compared to males [27]. One reason could be due to the small sample size. Concerning the occupation/employment level, the characteristics of the sample where more than half of the participants were not working (unemployed, early retirement, and retired) may explain this factor’s inability to explain the fatigue experienced.
Participation in many life areas might be restricted by increased fatigue. In the present study, mobility assistive devices have partly shown to have an association with fatigue, which implies that it is important to consider the access to mobility assistive devices in the healthcare system. Fatigue is a complex phenomenon [6], and therefore a number of factors that might be important for the understanding of fatigue should be included in the management of fatigue in this population. With this in mind, there is a need to consider the intersection of dimensions such as gender, age, cultural background, and occupational level.
In this retrospective registry study, fatigue was explored in relation to a set of factors that was taken from a clinical database. One limitation of using a clinical database was that it comprised predetermined variables, which restricted the choice of other factors of importance for the present study. Earlier qualitative studies [21, 22] have shown that life conditions related to conditions for daily occupations, social support, social network and municipal service were important for immigrants living with late effects of polio. These aspects could not be captured in the present study due to the use of predetermined variables.
Fatigue was assessed with the MFI-20 [5]. There are several questionnaires to measure fatigue [6, 25, 28, 29], but fatigue is a widely experienced symptom [5], that might vary rapidly [30]. The MFI-20 is valid and reliable for measuring fatigue in persons with PPS [25], and was therefore a suitable questionnaire to capture fatigue. Furthermore, a limited number of factors were explored in relation to fatigue in the present study due to the small sample size which is a limitation. Therefore, further research is needed to explore other relevant explanatory factors.
Conclusion
Persons not using mobility assistive devices and high age reported more fatigue. Therefore, fatigue could partly be explained by the extent of using mobility assistive devices and the people’s age. These two factors are important, but to understand the complex nature of fatigue, additional factors must be considered. Healthcare professionals should provide and demonstrate the importance of assistive devices to ensure management of fatigue in persons living with late effects of polio. This knowledge contributes with an additional piece in the puzzle to better understand fatigue among persons living with late effects of polio.
Acknowledgments
This study was supported by grants from the local Research and Development Council of Gothenburg and southern Bohuslän, and the Swedish Research Council for Health, and Working and Welfare (AGECAP 2013-2300). The authors are grateful to the polio team for gathering data and all the patients that have responded to the questionnaires. The authors are also grateful to Professor Synneve Dahlin-Ivanoff and PhD Anna-Lisa Thorén-Jönsson for valuable comments, and to Oscar Hammar, PhD Mathematical Statistics, for statistical consultation.
Availability of data and materials
Data will not be shared, because it is part of a clinical database.
Authors’ contributions
ISTS, KSS, and IOH conceived and designed the study. ISTS and IOH performed all the analyses. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable, the manuscript doesn’t contain any individual person’s data.
Ethics approval and consent to participate
The written informed patient consent has been approved by the Regional Ethical Review Board in Gothenburg, Sweden (Dnr 123-09). All participants signed an informed consent form, and received written and verbal information before participating in the clinical database.
Abbreviations
- EMG
Electromyogram
- GF
General fatigue
- MF
Mental fatigue
- MFI
Multidimensional fatigue inventory
- PF
Physical fatigue
- PPS
Post-polio syndrome
- RA
Reduced activity
- RM
Reduced motivation
References
- 1.On AY, Oncu J, Atamaz F, Durmaz B. Impact of post-polio-related fatigue on quality of life. J Rehabil Med. 2006;38(5):329–332. doi: 10.1080/16501970600722395. [DOI] [PubMed] [Google Scholar]
- 2.Schanke AK, Stanghelle JK. Fatigue in polio survivors. Spinal Cord. 2001;39(5):243–251. doi: 10.1038/sj.sc.3101147. [DOI] [PubMed] [Google Scholar]
- 3.Trojan DA, Cashman NR. Post-poliomyelitis syndrome. Muscle Nerve. 2005;31(1):6–19. doi: 10.1002/mus.20259. [DOI] [PubMed] [Google Scholar]
- 4.Jason LA, Evans M, Brown M, Porter N. What is Fatigue? Pathological and Nonpathological Fatigue. PMR. 2010;2(5):327–331. doi: 10.1016/j.pmrj.2010.03.028. [DOI] [PubMed] [Google Scholar]
- 5.Lundh Hagelin C, Wengström Y, Runesdotter S, Johan FC. The psychometric properties of the Swedish Multidimensional Fatigue Inventory MFI-20 in four different populations. Acta Oncol. 2007;46(1):97–104. doi: 10.1080/02841860601009430. [DOI] [PubMed] [Google Scholar]
- 6.Shen J, Barbera J, Shapiro CM. Distinguishing sleepiness and fatigue: focus on definition and measurement. Sleep Med Rev. 2006;10(1):63–76. doi: 10.1016/j.smrv.2005.05.004. [DOI] [PubMed] [Google Scholar]
- 7.Westbrook MT. A survey of post-poliomyelitis sequelae: Manifestations, effects on people’s lives and responses to treatment. Aust J Physiother. 1991;37(2):89–102. doi: 10.1016/S0004-9514(14)60534-1. [DOI] [PubMed] [Google Scholar]
- 8.Davis MP, Walsh D. Mechanisms of fatigue. J Support Oncol. 2010;8(4):164–174. [PubMed] [Google Scholar]
- 9.Fartu ERT, Gilhus NE. Post-polio syndrome an total health status in a perspective hospital study. Eur J Neurol. 2003;10:407–413. doi: 10.1046/j.1468-1331.2003.00613.x. [DOI] [PubMed] [Google Scholar]
- 10.Gawne ACHL. Post-polio syndrome: Pathophysiology and clinical management. Phys Rehabil Med. 1995;7:147–188. [Google Scholar]
- 11.Lund ML, Lexell J. Perceived participation in life situations in persons with late effects of polio. J Rehabil Med. 2008;40(8):659–664. doi: 10.2340/16501977-0237. [DOI] [PubMed] [Google Scholar]
- 12.Thoren-Jonsson AL, Grimby G. Ability and perceived difficulty in daily activities in people with poliomyelitis sequelae. J Rehabil Med. 2001;33(1):4–11. doi: 10.1080/165019701300006461. [DOI] [PubMed] [Google Scholar]
- 13.Santos Tavares Silva I. The dynamic nature of Participation - Experiences, strategies and conditions for occupations in daily life amongst persons with late effects of polio. Gothenburg: University od Gothenburg; 2016. [Google Scholar]
- 14.Borg K, Borg J, Edström L, Grimby L. Effects of excessive use of remaining muscle fibers in prior polio and LV lesion. Muscle Nerve. 1988;11(12):1219–1230. doi: 10.1002/mus.880111206. [DOI] [PubMed] [Google Scholar]
- 15.Perry J, Barnes G, Gronley JK. The Postpolio Syndrome: An Overuse Phenomenon. Clin Orthop Relat Res. 1988;233:145–162. [PubMed] [Google Scholar]
- 16.Grimby L, Tollbäck A, Müller U, Larsson L. Fatigue of chronically overused motor units in prior polio patients. Muscle Nerve. 1996;19(6):728–737. doi: 10.1002/(SICI)1097-4598(199606)19:6<728::AID-MUS7>3.0.CO;2-C. [DOI] [PubMed] [Google Scholar]
- 17.Sunnerhagen KS, Carlsson U, Sandberg A, Stålberg E, Hedberg M, Grimby G. Electrophysiologic evaluation of muscle fatigue development and recovery in late polio. Arch Phys Med Rehabil. 2000;81(6):770–776. doi: 10.1016/S0003-9993(00)90109-6. [DOI] [PubMed] [Google Scholar]
- 18.Malmusi D. Immigrants’ health and health inequality by type of integration policies in European countries. Eur J Public Health. 2015;25(2):293–299. doi: 10.1093/eurpub/cku156. [DOI] [PubMed] [Google Scholar]
- 19.Rechel B, Mladovsky P, Ingleby D, Mackenbach JP, McKee M. Migration and health in an increasingly diverse Europe. Lancet. 2013;381(9873):1235–1245. doi: 10.1016/S0140-6736(12)62086-8. [DOI] [PubMed] [Google Scholar]
- 20.Ostlund G, Wahlin A, Sunnerhagen KS, Borg K. Vitality among Swedish patients with post-polio: a physiological phenomenon. J Rehabil Med. 2008;40(9):709–714. doi: 10.2340/16501977-0253. [DOI] [PubMed] [Google Scholar]
- 21.Santos Tavares Silva I, Thorén-Jönsson A-L. Struggling to be part of Swedish society: Strategies used by immigrants with late effects of polio. Scand J Occup Ther. 2015;22(6):450–461. doi: 10.3109/11038128.2015.1057222. [DOI] [PubMed] [Google Scholar]
- 22.Santos-Tavares I, Thorén-Jönsson A-L. Confidence in the future and hopelessness: Experiences in daily occupations of immigrants with late effects of polio. Scand J Occupl Ther. 2013;20(1):9–20. doi: 10.3109/11038128.2012.660193. [DOI] [PubMed] [Google Scholar]
- 23.Thorén-Jönsson A-L. Adaptation and ability in daily occupation in people with poliomyelitis sequelae. Gothenburg: University of Gothenburg; 2000. [Google Scholar]
- 24.Vreede KS, Sunnerhagen KS. Characteristics of Patients at First Visit to a Polio Clinic in Sweden. PLoS ONE. 2016;11(3):e0150286. doi: 10.1371/journal.pone.0150286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Dencker A, Sunnerhagen KS, Taft C, Lundgren-Nilsson Å. Multidimensional fatigue inventory and post-polio syndrome – a Rasch analysis. Health Qual Life Outcomes. 2015;13:20. doi: 10.1186/s12955-015-0213-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ericsson A, Mannerkorpi K. Assessment of fatigue in patients with fibromyalgia and chronic widespread pain. Reliability and validity of the Swedish version of the MFI-20. Disabil Rehabil. 2007;29(22):1665–1670. doi: 10.1080/09638280601055782. [DOI] [PubMed] [Google Scholar]
- 27.Schwarz R, Krauss O, Hinz A. Fatigue in the general population. Oncologie. 2003;26(2):140–144. doi: 10.1159/000069834. [DOI] [PubMed] [Google Scholar]
- 28.Horemans HL, Nollet F, Beelen A, Lankhorst GJ. A comparison of 4 questionnaires to measure fatigue in postpoliomyelitis syndrome 1. Arch Phys Med Rehabil. 2004;85(3):392–398. doi: 10.1016/j.apmr.2003.06.007. [DOI] [PubMed] [Google Scholar]
- 29.Smets EMA, Garssen B, Bonke B, De Haes JCJM. The multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res. 1995;39(3):315–325. doi: 10.1016/0022-3999(94)00125-O. [DOI] [PubMed] [Google Scholar]
- 30.Whitehead L. The Measurement of Fatigue in Chronic Illness: A Systematic Review of Unidimensional and Multidimensional Fatigue Measures. J Pain Symptom Manage. 2009;37(1):107–128. doi: 10.1016/j.jpainsymman.2007.08.019. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data will not be shared, because it is part of a clinical database.